25,929 Result(s)
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Article
A new uncertainty processing method for trajectory prediction
In many domains, trajectory prediction a crucial task. Uncertain information, such as complementary and correlated information between multiple features, complex interactive information, weather and temperatur...
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Article
TAENet: transencoder-based all-in-one image enhancement with depth awareness
Recently, CNN-based all-in-one image enhancement methods have been proposed to solve multiple image degradation tasks. However, these CNN-based methods usually have two limitations. One limitation is that they...
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Probabilistic load forecasting based on quantile regression parallel CNN and BiGRU networks
In the dynamic smart grid landscape, accurate probabilistic forecasting of electric load is critical. This paper presents a novel 24-hour-ahead probabilistic load forecasting model by integrating quantile regr...
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On weak convergence of quantile-based empirical likelihood process for ROC curves
The empirical likelihood (EL) method possesses desirable qualities such as automatically determining confidence regions and circumventing the need for variance estimation. As an extension, a quantile-based EL ...
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Real-time salient object detection based on accuracy background and salient path source selection
Boundary and connectivity prior are common methods for detecting the image salient object. They often address two problems: 1) if the salient object touches the image boundary, the saliency of the object will ...
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Article
Open AccessPinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting
Power load data frequently display outliers and an uneven distribution of noise. To tackle this issue, we present a forecasting model based on an improved extreme learning machine (ELM). Specifically, we intro...
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Towards effective urban region-of-interest demand modeling via graph representation learning
Identifying the region’s functionalities and what the specific Point-of-Interest (POI) needs is essential for effective urban planning. However, due to the diversified and ambiguity nature of urban regions, th...
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Article
Transmission-guided multi-feature fusion Dehaze network
Image dehazing is an important direction of low-level visual tasks, and its quality and efficiency directly affect the quality of high-level visual tasks. Therefore, how to quickly and efficiently process hazy...
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Event-Driven Heterogeneous Network for Video Deraining
Restoring clear frames from rainy videos poses a significant challenge due to the swift motion of rain streaks. Traditional frame-based visual sensors, which record dense scene content synchronously, struggle ...
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Effective multi-scale enhancement fusion method for low-light images based on interest-area perception OCTM and “pixel healthiness” evaluation
Low-light images suffer from low contrast and low dynamic range. However, most existing single-frame low-light image enhancement algorithms are not good enough in terms of detail preservation and color express...
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Article
CoFF-CHP: coarse-to-fine filters with concept heuristic prompt for few-shot relation classification
Few-shot relation classification (RC) is a crucial task that aims to identify the relationships between entity pairs with limited mentions. However, this task is challenging due to the insufficient amount of a...
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Packet header-based reweight-long short term memory (Rew-LSTM) method for encrypted network traffic classification
With the development of Internet technology, cyberspace security has become a research hotspot. Network traffic classification is closely related to cyberspace security. In this paper, the problem of classific...
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Article
Preference detection of the humanoid robot face based on EEG and eye movement
The face of a humanoid robot can affect the user experience, and the detection of face preference is particularly important. Preference detection belongs to a branch of emotion recognition that has received mu...
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TOCOL: improving contextual representation of pre-trained language models via token-level contrastive learning
Self-attention, which allows transformers to capture deep bidirectional contexts, plays a vital role in BERT-like pre-trained language models. However, the maximum likelihood pre-training objective of BERT may...
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Retraction Note: Editorial: neural computing in next-generation virtual reality technology
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Article
Spatially-Varying Illumination-Aware Indoor Harmonization
In this paper, we address the problem of spatially-varying illumination-aware indoor harmonization. Existing image harmonization works either focus on extracting no more than 2D information (e.g., low-level st...
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Article
The error sample feature compensation method for improving the robustness of underwater classification and recognition models
With the intensification of ocean exploration and development in recent years, the navigation equipment in the marine environment has become increasingly diversified, making the marine environment more complex...
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Article
Correction: Learning sample-aware threshold for semi-supervised learning
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Article
Incorporating self-attentions into robust spatial-temporal graph representation learning against dynamic graph perturbations
This paper proposes a Robust Spatial-Temporal Graph Neural Network (RSTGNN), which overcomes the limitations faced by graph-based models against dynamic graph perturbations using robust spatial-temporal self-a...
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Article
Oriented R-CNN and Beyond
Currently, two-stage oriented detectors are superior to single-stage competitors in accuracy, but the step of generating oriented proposals is still time-consuming, thus hindering the inference speed. This pap...
